There are 1 repository under cityscapes topic.
The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919
Official PyTorch implementation of SegFormer
Add bisenetv2. My implementation of BiSeNet
DeepLabv3 and DeepLabv3+ with pretrained weights for Pascal VOC & Cityscapes
LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)
Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, ContextNet, FPENet, etc.)
Support PointRend, Fast_SCNN, HRNet, Deeplabv3_plus(xception, resnet, mobilenet), ContextNet, FPENet, DABNet, EdaNet, ENet, Espnetv2, RefineNet, UNet, DANet, HRNet, DFANet, HardNet, LedNet, OCNet, EncNet, DuNet, CGNet, CCNet, BiSeNet, PSPNet, ICNet, FCN, deeplab)
Understanding Convolution for Semantic Segmentation
[ICLR 2020] "FasterSeg: Searching for Faster Real-time Semantic Segmentation" by Wuyang Chen, Xinyu Gong, Xianming Liu, Qian Zhang, Yuan Li, Zhangyang Wang
This is Pytorch re-implementation of our CVPR 2020 paper "Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation" (https://arxiv.org/abs/1911.10194)
Papers and Benchmarks about semantic segmentation, instance segmentation, panoptic segmentation and video segmentation
ICCV2021 (Oral) - Exploring Cross-Image Pixel Contrast for Semantic Segmentation
[CVPR 2021] Self-supervised depth estimation from short sequences
TensorFlow-based implementation of "ICNet for Real-Time Semantic Segmentation on High-Resolution Images".
Pytorch code for semantic segmentation using ERFNet
This repository contains the source code of our work on designing efficient CNNs for computer vision
PytorchAutoDrive: Segmentation models (ERFNet, ENet, DeepLab, FCN...) and Lane detection models (SCNN, PRNet, RESA, LSTR, BézierLaneNet...) based on PyTorch with fast training, visualization, benchmarking & deployment help
[ICCV19] AdaptIS: Adaptive Instance Selection Network, https://arxiv.org/abs/1909.07829
TensorFlow-based implementation of "Pyramid Scene Parsing Network".
Implementation of Our ECCV2020-work: Improving Semantic Segmentation via Decoupled Body and Edge Supervision
IJCAI2020 & IJCV 2021 :city_sunrise: Unsupervised Scene Adaptation with Memory Regularization in vivo
SOTA Semantic Segmentation Models in PyTorch
📸 PyTorch implementation of MobileNetV3 for real-time semantic segmentation, with pretrained weights & state-of-the-art performance
Official PyTorch implementation of Fully Attentional Networks
LightNet++: Boosted Light-weighted Networks for Real-time Semantic Segmentation
CGNet: A Light-weight Context Guided Network for Semantic Segmentation [IEEE Transactions on Image Processing 2020]
Unofficial tensorflow implementation of real-time scene image segmentation model "BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation"
Fully Convolutional HarDNet for Segmentation in Pytorch
Criss-Cross Attention (2d&3d) for Semantic Segmentation in pure Pytorch with a faster and more precise implementation.
[Preprint] SeMask: Semantically Masked Transformers for Semantic Segmentation.
Code, data and benchmark from the paper "Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming" (NeurIPS 2019 ML4AD)
mIOU=80.02 on cityscapes. My implementation of deeplabv3+ (also know as 'Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation' based on the dataset of cityscapes).
Code for Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells, CVPR '19
[CVPR 2022] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels
Depth-wise Asymmetric Bottleneck for Real-time Semantic Segmentation (BMVC2019)